Network quality measurement method and system

ABSTRACT

A network quality measurement method and system are provided. In the method, a movement path and a movement speed of a vehicle device are determined according to a size of a space and an endurance time of the vehicle device, and the vehicle device is controlled to move on the movement path at the movement speed. During a movement of the vehicle device, a network quality in the space is measured according to a measurement frequency to generate network quality data. Whether the network quality in the space is changed is determined according to the network quality data. Whether there is an obstacle around the vehicle device is detected. When it is determined that the network quality in the space is changed or the obstacle is detected around the vehicle device, at least one of the movement path, the movement speed, and the measurement frequency is adjusted.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of Taiwan applicationserial no. 110145224, filed on Dec. 3, 2021. The entirety of theabove-mentioned patent application is hereby incorporated by referenceherein and made a part of this specification.

TECHNICAL FIELD

The disclosure relates to a quality measurement method and system, andrelates to a network quality measurement method and system.

BACKGROUND

There is an increasing demand for high-bandwidth and low-latency mobilenetwork deployment in application fields such as drone sports, droneperformances, or smart factories. In particular, drone competitions havereceived much attention in recent years and have become one of the mostpopular events. There are now FAI (Fédération AéronautiqueInternationale), DRL (Drone Racing League) and other competition leaguesregularly holding competitions around the world, which has promotedbusiness opportunities for sports broadcasting and peripheraladvertising.

The images used by the current competitive drones are analog signalswith low screen resolution and full of noise, and therefore it isdifficult to meet the demand for rebroadcasting high-quality images. Thedeployment of 5G private network may solve the above issues. High-speedbandwidth data performance and millisecond-level latency performancemean that more data may be handled and the quality of image transmissionis simultaneously improved, thus bringing clear and shocking imageperformance to significantly enhance entertainment effect andexperience.

The traditional method of network deployment is to collect measurementdata by means of manual fixed-point sampling through a frequency scanneror running a program. However, using this method for network deploymentin the application field of 5G private network results in the followingissues: manual fixed-point sampling may not measure the network qualityin three-dimensional (3D) space, and fixed-point measurement is slow andinefficient. Moreover, after measuring network quality, how to apply thenetwork quality to network deployment adjustments or to efficientlypresent the good and bad distribution of network quality in the entiremeasurement space is another issue worthy of attention.

SUMMARY

An embodiment of the disclosure provides a network quality measurementmethod suitable for a vehicle device. The method includes determining amovement path and a movement speed of a vehicle device according to asize of a space and an endurance time of the vehicle device, andcontrolling the vehicle device to move on the movement path at themovement speed; measuring a network quality in the space according to ameasurement frequency during a movement of the vehicle device togenerate network quality data; determining whether the network qualityin the space is changed according to the network quality data; detectingwhether there is an obstacle around the vehicle device; and adjusting atleast one of the movement path, the movement speed, and the measurementfrequency when it is determined that the network quality in the space ischanged or the obstacle is detected around the vehicle device.

An embodiment of the disclosure provides a network quality measurementsystem including a vehicle device. The vehicle device includes acontroller, a network quality measurer, and an obstacle detector. Thecontroller is configured to determine a movement path and a movementspeed of the vehicle device according to a size of a space and anendurance time of the vehicle device, and the vehicle device iscontrolled to move on the movement path at the movement speed. Thenetwork quality measurer is coupled to the controller and configured tomeasure a network quality in the space according to a measurementfrequency during a movement of the vehicle device to generate networkquality data. The obstacle detector is coupled to the controller andconfigured to detect whether there is an obstacle around the vehicledevice. The controller determines whether the network quality in thespace is changed according to the network quality data. When thecontroller determines that the network quality in the space is changedor the obstacle detector detects the obstacle around the vehicle device,the controller adjusts at least one of the movement path, the movementspeed, and the measurement frequency.

Several exemplary embodiments accompanied with figures are described indetail below to further describe the disclosure in details.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are included to provide further understanding,and are incorporated in and constitute a part of this specification. Thedrawings illustrate exemplary embodiments and, together with thedescription, serve to explain the principles of the disclosure.

FIG. 1 is a block diagram of a network quality measurement system shownaccording to an embodiment of the disclosure.

FIG. 2 is a flowchart of a network quality measurement method shownaccording to an embodiment of the disclosure.

FIG. 3 is a flowchart of a method for converting data from a time domainto a space domain shown according to an embodiment of the disclosure.

FIG. 4 is a flowchart of a method for visualizing a measurement resultshown according to an embodiment of the disclosure.

FIG. 5 is a stereoscopic view of the visualization of a measurementresult shown according to an embodiment of the disclosure.

FIG. 6 is a stereoscopic view of the visualization of a measurementresult shown according to another embodiment of the disclosure.

DETAILED DESCRIPTION OF DISCLOSED EMBODIMENTS

For the private network application field where network quality ishighly demanded, the existing measurement methods may not be able toobtain network status in stereoscopic space, thus making the deploymentof an aerial vehicle difficult. In addition, the efficiency of theexisting measurement methods is not good, and the needs of rapidadjustment and deployment in line with site changes are not readily met.To solve these two major issues, the embodiments of the disclosureprovide a network quality measurement method and system. This methodmeasures the network quality in the space during the movement of theaerial vehicle using a network quality measurer, and detects theenvironment around the aerial vehicle using an obstacle detector. Byobtaining the above information, it may be determined whether thenetwork quality in the space is changed and whether there is an obstaclearound the aerial vehicle, and in the presence of at least one of theabove, the deployment is adjusted to enhance the measurement for regionswith poor network quality. In addition, this method may also visualize ameasurement result combined with images, thereby improving theefficiency of viewing the measurement result and making the efficiencyof network deployment clear at a glance.

FIG. 1 is a block diagram of a network quality measurement system shownaccording to an embodiment of the disclosure. Please refer to FIG. 1 , anetwork quality measurement system 10 of the present embodiment includesa vehicle device 100. The vehicle device 100 is, for example, anunmanned aerial vehicle, and may be a drone, but is not limited thereto.In the present embodiment, the vehicle device 100 includes a controller102, a network quality measurer 104, and an obstacle detector 106.

The controller 102 is, for example, a central processing unit (CPU) or aprogrammable general-use or special-use microprocessor, digital signalprocessor (DSP), programmable controller, application-specificintegrated circuit (ASIC), or other similar devices or a combination ofthese devices.

The network quality measurer 104 may measure network information such asavailable bandwidth, response latency, network jitter, packet loss rate,received signal strength indication (RSSI), etc., and is coupled to thecontroller 102, and transmits the measured data to the controller 102,so that the controller 102 may determine whether the network quality ofthe surrounding environment of the vehicle device 100 is changed.

The obstacle detector 106 is, for example, a radar, a sound wave sensingdevice, or an optical sensing device, such as an element having thefunction of sensing the distance of an object such as an optical radaradopting optical ranging (Light Detection And Ranging, LiDAR), adepth-of-field camera, an image capture device, etc. In the presentembodiment, the obstacle detector 106 may detect the surroundingenvironment, and is coupled to the controller 102, and transmits thedetected data to the controller 102, so that the controller 102 maydetermine whether there is an obstacle in the surrounding environment ofthe vehicle device 100.

In an embodiment, the vehicle device 100 includes a locator 108, a timer110, and a memory 112.

The locator 108 obtains the size (including length, width, and height)of the space to be measured by the vehicle device 100 using apositioning system (for example, Global Positioning System (GPS),Real-Time Kinematic (RTK) positioning system, or Ultra-Wideband (UWB)positioning system, etc.), and is coupled to the controller 102, so thatthe controller 102 obtains the coordinate position of the vehicle device100 via the locator 108 according to the size of the space and themeasurement frequency.

The timer 110 is coupled to the controller 102 and generates a clocksignal and outputs the clock signal to the controller 102, so that thecontroller 102 obtains the measurement timestamp of the currentmeasurement network quality according to the clock signal.

The memory 112 is, for example, any type of random-access memory (RAM),read-only memory (ROM), flash memory, hard drive, a similar element, ora combination of the elements. In the present embodiment, the memory 112is coupled to the controller 102, and the controller 102 integrates thecoordinate information and the measurement time stamp to generate ameasurement record, and stores the measurement record in the memory 112.The measurement record includes movement speed, movement path,measurement frequency, and network quality data corresponding to thecoordinate information and the measurement timestamp.

In yet another embodiment, the vehicle device 100 includes an imagecapture device 114, and the network quality measurement system 10includes a terminal device 200. The terminal device 200 is, for example,a notebook computer, a tablet computer, a smart phone, or a personaldigital assistant (PDA), but is not limited thereto. In the presentembodiment, the terminal device 200 includes an image processor 202 andan image display 204.

The image capture device 114 is, for example, an electronic devicehaving a function of capturing or shooting images, such as a camera oran infrared or visible light camera. In the present embodiment, theimage capture device 114 captures an image during the movement of thevehicle device 100.

The image processor 202 is, for example, a central processing unit (CPU)or a general-purpose or special-purpose programmable microprocessor,digital signal processor (DSP), programmable controller,application-specific integrated circuit (ASIC), or other similar devicesor a combination of the above devices, but is not limited thereto. Inthe present embodiment, the image processor 202 is coupled to the memory112 and the image capture device 114. The image processor 202 may obtainvarious data from the memory 112 and obtain an image from the imagecapture device 114 to execute the method for visualizing a measurementresult of an embodiment of the disclosure to generate a visualizedimage.

The image display 204 is, for example, a device having a displayfunction such as a liquid-crystal display panel (LCD) or an organiclight-emitting diode (OLED), but is not limited thereto. In the presentembodiment, the image display 204 is coupled to the image processor 202and displays a visualized image generated by the image processor 202.

FIG. 2 is a flowchart of a network quality measurement method shownaccording to an embodiment of the disclosure. Referring to both FIG. 1and FIG. 2 , a method 20 of the present embodiment is applicable to thenetwork quality measurement system 10 of FIG. 1 . The following is adescription of the detailed steps of the network quality measurementmethod of the disclosure in conjunction with the operation relationshipbetween the devices in the network quality measurement system 10.

First, in step S200, the controller 102 determines the movement path andmovement speed of the vehicle device 100 according to the size of thespace and the endurance time of the vehicle device 100. The controller102 obtains the size of the space to be measured by the vehicle device100 via the locator 108, and according to the size of the space and theendurance time of the vehicle device 100, estimates flight parameterssuch as movement speed, detour density, detour sequence, number ofrepetitions, pause mode, and interval of the vehicle device 100. In anembodiment, the flight time of the vehicle device 100 is a certainproportion (for example, 50%) of the maximum endurance time to retainthe flexibility of dynamically changing the measurement methodsubsequently. In an embodiment, the movement path may first go aroundthe XY plane at a fixed height and then at a different height, but isnot limited thereto.

In step S202, the controller 102 controls the vehicle device 100 to moveon the movement path at the movement speed. During the movement of thevehicle device 100, the obstacle detector 106 and the network qualitymeasurer 104 may simultaneously perform step S204 and step S208respectively (exemplified as such in the present embodiment). In anembodiment, the obstacle detector 106 and the network quality measurer104 may also perform step S204 and step S208 respectively in sequence,and vice versa.

In step S204, the obstacle detector 106 detects whether there is anobstacle around the vehicle device 100. When the obstacle detector 106detects that there is an obstacle around the vehicle device 100, stepS206 is performed, and the controller 102 adjusts at least one of themovement path, the movement speed, and the measurement frequency. Then,returning to step S202, the controller 102 controls the vehicle device100 to move on the adjusted movement path at the adjusted movementspeed.

When the obstacle detector 106 detects that an obstacle is within apredetermined distance from the vehicle device 100, the controller 102obtains the obstacle distance between the vehicle device 100 and theobstacle from the obstacle detector 106. Next, the controller 102adjusts at least one of the movement path, the movement speed, and themeasurement frequency according to the distance of the obstacle (forexample, reducing the movement speed or adjusting the detour density),and updates the measurement record in the memory 112 according to atleast one of the adjusted movement path, movement speed, and measurementfrequency and the obstacle distance. In an embodiment, the predetermineddistance may be a radius of 5 meters centered on the vehicle device 100or any value, and the disclosure is not limited in this regard.

In an embodiment, when the controller 102 determines that the obstaclemay collide with the vehicle device 100, the controller 102 initiates alocal path planning method (for example, Dynamic Window Approach (DWA))to avoid the obstacle. This method, in conjunction with increasing thedetour density of the vehicle device 100, may increase the precision ofdetour in a region having an obstacle, thereby collecting densermeasurement data.

In step S208, the network quality measurer 104 measures the networkquality in the space according to the measurement frequency to generatenetwork quality data. Next, in step S210, the controller 102 determineswhether the network quality in the space is changed according to thenetwork quality data. When the controller 102 determines that thenetwork quality in the space is changed, step S206 is performed, and thecontroller 102 adjusts at least one of the movement path, the movementspeed, and the measurement frequency. Then, returning to step S202, thecontroller 102 controls the vehicle device 100 to move on the adjustedmovement path at the adjusted movement speed.

The controller 102 determines whether the measurement result of thenetwork quality at the time is significantly lower than a certainthreshold or has a significant change. Moreover, when the controller 102determines that the measurement result of the network quality at thattime is significantly lower than a certain threshold value or has asignificant change, the controller 102 adjusts at least one of themovement path, the movement speed, and the measurement frequency (suchas reducing the movement speed or adjusting the detour density). In anembodiment, the change may be directly determined via a record ofchanges over time during the movement of the vehicle device 100. Inanother embodiment, the changes may also be determined after themovement record of the vehicle device 100 and the measurement record ofthe network quality measurer 104 are synchronized first and thenconverted to a quality measurement value spatial distribution record.This method of converting data from the time domain to the space domainis described in detail in FIG. 3 .

Returning to step S204 and step S210, when the obstacle detector 106detects that there is no obstacle around the vehicle device 100 or thecontroller 102 determines that the network quality in the space is notchanged, step S202 is repeated, wherein the vehicle device 100 continuesto move on the original movement path at the original movement speed,and the obstacle detector 106 and the network quality measurer 104continue to perform detection and measurement until a return-to-homecondition is met (for example, the vehicle device 100 completes thedetour), and the vehicle device 100 executes the return-to-home.

In an embodiment, the controller 102 receives an external command,adjusts at least one of the movement path, the movement speed, and themeasurement frequency according to the external command, and updates themeasurement record in the memory 112 according to at least one of theadjusted movement path, movement speed, and measurement frequency. Then,the controller 102 controls the vehicle device 100 to move on theadjusted movement path at the adjusted movement speed.

FIG. 3 is a flowchart of a method for converting data from a time domainto a space domain shown according to an embodiment of the disclosure.

During the measurement process of the vehicle device 100, in addition torecording various data related to the vehicle device 100 (such as speed,coordinates, detour status, obstacle distance, etc.), the memory 112also records various data measured by the network quality measurer 104(for example, available bandwidth, response latency, network jitter,packet loss rate, RSSI, etc.) In an embodiment, the data are allrecorded over time, and each is independently stored in the memory 112.

In the present embodiment, the determination of whether the networkquality is changed in step S210 in FIG. 2 needs to be performed afterthe data recorded over time is converted into a spatially varyingquality measurement value spatial distribution record. The controller102 samples and transforms the network quality data of the vehicledevice 100 in the space according to a predetermined sub-region size todetermine whether the network quality in the space is changed.

Referring to both FIG. 1 and FIG. 3 , a method 30 of the presentembodiment is applicable to the network quality measurement system 10 ofFIG. 1 . The following is a description of the detailed steps of themethod of converting data from time domain to space domain of thedisclosure in conjunction with the operation relationship between thedevices in the network quality measurement system 10.

First, in step S300, the controller 102 cuts the space into a pluralityof sub-regions according to the sub-region size. For example, thecontroller 102 cuts the space to be measured into M*N*K sub-regionsaccording to the sub-region size Gsize, and establishes a coordinatesystem corresponding to M*N*K, and each of the sub-regions has acorresponding sub-region coordinate index Gi=(x,y,z). In an embodiment,one space of 50 meters by 50 meters by 20 meters is measured out, andthe sub-region size Gsize may be 125 cubic meters (5 meters by 5 metersby 5 meters) or any value, but the disclosure not limited thereto. In anembodiment, M, N, and K are 10, 10, and 4, and all are positiveintegers.

Then, in step S302, the controller 102 correspondingly obtains thecoordinate information of the vehicle device 100 according to themeasurement timestamp. In an embodiment, the coordinate information ofthe vehicle includes a record of time and the coordinate parameter ofthe vehicle at that point in time. The coordinate parameter may be aglobal coordinate system (such as GPS longitude, latitude, andaltitude), or the distance value of a three-dimensional coordinatesystem relative to a certain origin. In an embodiment, if thecoordinates used are global coordinates (such as GPS), the displacementdistance between the coordinates may be obtained via calculation.

In step S304, the controller 102 determines that the vehicle device 100falls in each of the plurality of sub-regions according to thecoordinate information, so as to obtain the timestamp corresponding tothe vehicle device 100 entering and leaving each of the sub-regions inthe measurement timestamp. Then, in step S306, the controller 102classifies the network quality data according to the timestamp, so thatthe classified network quality data correspond to each of thesub-regions. In an embodiment, the controller 102 uses the timestamp ofentering and leaving each of the sub-regions as an index, and calculatesand obtains the sub-region coordinate index corresponding to the networkquality data recorded in the memory 112 according to the distance valueobtained via the coordinate parameter and the sub-region size Gsize, andcorresponds the recorded network quality data to each of thesub-regions.

In step S308, the controller 102 calculates at least one qualitymeasurement value corresponding to each of the sub-regions according tothe classified network quality data, and generates a spatial measurementrecord matrix corresponding to the at least one quality measurementvalue. In some embodiments, the indicators used to measure networkquality are: packet response time, packet loss rate, network jitter,available bandwidth, signal-to-interference plus noise ratio, RSSI, etc.The calculation method may be to calculate the average value of thenetwork quality data in the sub-regions (for example, calculate theaverage response time of 10 packets via an arithmetic average method);or calculate the score value (for example, the score value of 1 to 20)via a quantified calculation; or, after the score values of variousmeasurement data are calculated, calculate a single quality measurementvalue by adding weights according to application requirements.

In the present embodiment, the conversion of the data recorded over timeinto the spatially varying quality measurement value spatialdistribution record mainly has the following two functions:

First, the controller 102 may compare at least one quality measurementvalue of an adjacent sub-region in the three-dimensional space, and whenthe difference of the at least one quality measurement value of theadjacent sub-region is greater than a threshold value, the controller102 determines that the network quality in the space is changedsignificantly. Significant changes in network quality may be due tosignal obscuration or signal interference. In an embodiment, themovement mode of the vehicle device 100 or the conditions of themeasurement density may be triggered to be adjusted in the measurementprocess to enhance the measurement in this region. Moreover, thecontroller 102 may also adjust the initial sub-region size Gsize toobtain a denser sub-region to calculate a more accurate gradient. Thisapproach may solve the issue that the measurement change of the movementdirection of the non-vehicle device 100 cannot be detected due to thelack of the concept of space when determining from time alone.

Second, the terminal device 200 may also adopt the quality measurementvalue spatial distribution record to establish the measurement qualitydistribution of the entire stereoscopic space, and present the qualitymeasurement value of each of the sub-regions in a specific color ormaterial. This method of visualizing a measurement result is describedin detail in FIG. 4 .

FIG. 4 is a flowchart of a method for visualizing a measurement resultshown according to an embodiment of the disclosure. Referring to bothFIG. 1 and FIG. 4 , a method 40 of the present embodiment is applicableto the network quality measurement system 10 of FIG. 1 . The followingis a description of the detailed steps of the method of visualizing ameasurement result of the disclosure in conjunction with the operationrelationship between the devices in the network quality measurementsystem 10.

First, in step S400, the image processor 202 receives an image from theimage capture device 114, and obtains the image timestamp of the image.In step S402, the image processor 202 corresponds the coordinateinformation of the vehicle device 100 to the image timestamp. In stepS404, the image processor 202 obtains the attitude parameter of thevehicle device 100 and the lens parameter of the image capture device114 according to the image.

In step S406, the image processor 202 calculates the angle of viewposition in the three-dimensional space according to the attitudeparameter and the lens parameter. Next, in step S408, the imageprocessor 202 obtains at least one quality measurement valuecorresponding to a plurality of sub-regions in the angle of viewposition according to the spatial measurement record matrix. In stepS410, the image processor 202 classifies at least one qualitymeasurement value so that the at least one quality measurement valuecorresponds to a color mark of different colors or a material mark ofdifferent materials according to the category. In step S412, the imageprocessor 202 combines at least one quality measurement value aftercorresponding to the color mark or the material mark and the image togenerate a visualized image.

In an embodiment, the image processor 202 may determine the currentlyvisible range of the visualized image according to the lens parameter(such as the angle of view), vehicle coordinates, and vehicle attitude,thereby determining the quality measurement value of the sub-region thatneeds to be rendered. In an embodiment, when the image processor 202draws the quality measurement value of the visualized image, theposition and size of the visualized material in the planar image thatshould be drawn may be calculated using a perspective projection method.In an embodiment, the coordinate parameter may be a global coordinatesystem (such as GPS longitude, latitude, and altitude), or the distancevalue of a three-dimensional coordinate system relative to a certainorigin. The attitude parameter may be roll angle, pitch angle, and yawangle of the aircraft relative to the coordinate system at the time, andin an embodiment, may be represented by three Yura angle values or in aquaternion manner. In an embodiment, if the angle of the lens may bedifferent from the heading of the aircraft due to the installationmethod or the rotation of the lens itself, the attitude parameter alsoincludes the rotation angle of the lens itself.

In step S414, the image display 204 displays the visualized imagegenerated by the image processor 202. For example, FIG. 5 is a mixedreality view of the visualization of a measurement result shownaccording to an embodiment of the disclosure. In a visualized image 50,different texture or color can be used to render onto the image todifferent quality measurement values, which may visually present themeasurement result in the image.

In an embodiment, when an image update is received from the imagecapture device 114 (for example, when an image record file is played ora streaming image is updated), steps S400 to S414 are repeated.

In an embodiment, when the coordinate information and attitude parametercorresponding to the image timestamp of the image are received from theimage capture device 114, the image processor 202 simultaneouslycalculates and updates the angle of view position in thethree-dimensional space, and changes the visualized image that needs tobe drawn in the image.

In an embodiment, in the process of performing the visualization of ameasurement result, if the image processor 202 finds that there isinformation about the obstacle distance recorded in the memory 112, orother vehicle control behavior information related to enhanced regionmeasurement (such as speed change, increase of detour points) oradjustment of measurement information interval, the image processor 202also enhances the presentation effect of this region in the process ofvisualizing the measurement result. Therefore, when converting data fromtime domain to space domain, the controller 102 determines whether toadjust the sub-region size Gsize for cutting the measurement spaceaccording to information such as obstacle distance, movement speed, ormeasurement frequency, so that the image processor 202 may dynamicallychange the visualization of the measurement result.

In an embodiment, the image processor 202 may directly obtain at leastone quality measurement value corresponding to a plurality ofsub-regions in the space from the spatial measurement record matrix inthe memory 112, and present the at least one quality measurement valueusing different colors or materials to generate a visualized image. Forexample, FIG. 6 is a stereoscopic view of the visualization of ameasurement result shown according to another embodiment of thedisclosure. In a visualized image 60, different material renderingsrepresent different quality measurement values, which may visuallypresent the measurement result in the space.

The specific order and/or hierarchy of the steps in the method of anembodiment of the disclosure is an exemplary approach. Based on designpreferences, the specific order or hierarchy of the steps of thedisclosed method or process may be rearranged while remaining within thescope of the embodiments of the disclosure. Therefore, those of ordinaryskill in the art will understand that the methods and techniques of theembodiments of the disclosure present various steps or actions in asample order, and the embodiments of the disclosure are not limited tothe specific order or hierarchy presented, unless explicitly statedotherwise.

Based on the above, when an obstacle around the aerial vehicle orsignificant changes in the network quality in space are detected, thenetwork quality measurement method and system of the disclosure mayautomatically change the movement path and movement speed of the aerialvehicle or the measurement frequency of network quality to enhance themeasurement for regions with poor network quality. Therefore, networkdeployment may be dynamically adjusted and network time may be reduced.In addition, this method may also combine images to visually present ameasurement result, thereby efficiently presenting the good and baddistribution of network quality in the entire measurement space.

It will be apparent to those skilled in the art that variousmodifications and variations may be made to the structure of thedisclosed embodiments without departing from the scope or spirit of thedisclosure. In view of the foregoing, it is intended that the disclosurecover modifications and variations of this disclosure provided they fallwithin the scope of the following claims and their equivalents.

What is claimed is:
 1. A network quality measurement method suitable fora vehicle device, comprising: determining a movement path and a movementspeed of a vehicle device according to a size of a space and anendurance time of the vehicle device, and controlling the vehicle deviceto move on the movement path at the movement speed; measuring a networkquality in the space according to a measurement frequency during amovement of the vehicle device to generate network quality data;determining whether the network quality in the space is changedaccording to the network quality data; detecting whether there is anobstacle around the vehicle device; and adjusting at least one of themovement path, the movement speed, and the measurement frequency when itis determined that the network quality in the space is changed or theobstacle is detected around the vehicle device.
 2. The network qualitymeasurement method of claim 1, further comprising: obtaining the size ofthe space; obtaining a coordinate information of the vehicle deviceaccording to the size of the space and the measurement frequency;obtaining a measurement timestamp measuring a current network qualityaccording to a clock signal generated by the vehicle device; andintegrating the coordinate information and the measurement timestamp togenerate a measurement record, and the measurement record comprises themovement speed, the movement path, the measurement frequency, and thenetwork quality data corresponding to the coordinate information and themeasurement timestamp.
 3. The network quality measurement method ofclaim 2, wherein the step of adjusting at least one of the movementpath, the movement speed, and the measurement frequency when detectingthat there is the obstacle around the vehicle device comprises:obtaining, when the obstacle detector detects that the obstacle iswithin a predetermined distance from the vehicle device, an obstacledistance between the vehicle device and the obstacle, adjusting at leastone of the movement path, the movement speed, and the measurementfrequency according to the obstacle distance, and updating themeasurement record according to at least one of the adjusted movementpath, movement speed, and measurement frequency and the obstacledistance.
 4. The network quality measurement method of claim 2, furthercomprising: receiving an external command, adjusting at least one of themovement path, the movement speed, and the measurement frequencyaccording to the external command, and updating the measurement recordaccording to at least one of the adjusted movement path, movement speed,and measurement frequency.
 5. The network quality measurement method ofclaim 2, wherein the step of determining whether the network quality inthe space is changed according to the network quality data comprises:sampling and transforming the network quality data of the vehicle devicein the space according to a predetermined sub-region size to determinewhether the network quality in the space is changed.
 6. The networkquality measurement method of claim 5, further comprising: cutting thespace into a plurality of sub-regions according to the sub-region size;obtaining the coordinate information of the vehicle device according tothe measurement timestamp correspondingly; determining that the vehicledevice falls in each of the plurality of sub-regions according to thecoordinate information, so as to obtain a timestamp corresponding to thevehicle device entering and leaving each of the sub-regions in themeasurement timestamp; classifying the network quality data according tothe timestamp, so that the classified network quality data correspondsto each of the sub-regions; and calculating at least one qualitymeasurement value corresponding to each of the sub-regions according tothe classified network quality data, and generating a spatialmeasurement record matrix corresponding to the at least one qualitymeasurement value.
 7. The network quality measurement method of claim 6,wherein the at least one quality measurement value of an adjacentsub-region is compared, and when a difference between the at least onequality measurement value of the adjacent sub-region is greater than athreshold value, it is determined that the network quality in the spaceis changed.
 8. The network quality measurement method of claim 6,wherein the at least one quality measurement value of an adjacentsub-region is compared, and when a difference between the at least onequality measurement value of the adjacent sub-region is greater than athreshold value, the sub-region size is adjusted, and the space is cutinto a plurality of sub-regions according to the adjusted sub-regionsize.
 9. The network quality measurement method of claim 6, furthercomprising: capturing an image during the movement via the vehicledevice.
 10. The network quality measurement method of claim 9, furthercomprising: receiving the image and obtaining an image timestamp of theimage; corresponding the coordinate information of the vehicle device tothe image timestamp; obtaining an attitude parameter of the vehicledevice and a lens parameter according to the image; calculating an angleof view position in a three-dimensional space according to the attitudeparameter and the lens parameter; obtaining the at least one qualitymeasurement value corresponding to a plurality of sub-regions in theangle of view position according to the spatial measurement recordmatrix; classifying the at least one quality measurement value so thatthe at least one quality measurement value corresponds to a color markof different colors or a material mark of different materials accordingto a category; combining the at least one quality measurement valueafter corresponding to the color mark or the material mark and the imageto generate a visualized image; and displaying the visualized image. 11.A network quality measurement system, comprising: a vehicle device,comprising: a controller configured to determine a movement path and amovement speed of a vehicle device according to a size of a space and anendurance time of the vehicle device and control the vehicle device tomove on the movement path at the movement speed; a network qualitymeasurer coupled to the controller and configured to measure a networkquality in the space according to a measurement frequency during amovement of the vehicle device to generate network quality data; and anobstacle detector coupled to the controller and configured to detectwhether there is an obstacle around the vehicle device, wherein thecontroller determines whether the network quality in the space ischanged according to the network quality data, and when the controllerdetermines that the network quality in the space is changed or theobstacle detector detects the obstacle is around the vehicle device, thecontroller adjusts at least one of the movement path, the movementspeed, and the measurement frequency.
 12. The network qualitymeasurement system of claim 11, wherein the vehicle device furthercomprises: a locator coupled to the controller and configured to obtainthe size of the space, and the controller obtains a coordinateinformation of the vehicle device via the locator according to the sizeof the space and the measurement frequency; a timer coupled to thecontroller and configured to generate a clock signal, and the controllerobtains a measurement timestamp measuring a current network qualityaccording to the clock signal; and a memory coupled to the controller,wherein the controller integrates the coordinate information and themeasurement timestamp to generate a measurement record, and stores themeasurement record in the memory, and the measurement record comprisesthe movement speed, the movement path, the measurement frequency, andthe network quality data corresponding to the coordinate information andthe measurement timestamp.
 13. The network quality measurement system ofclaim 12, wherein when the obstacle detector detects that the obstacleis within a predetermined distance from the vehicle device, thecontroller obtains an obstacle distance between the vehicle device andthe obstacle, adjusts at least one of the movement path, the movementspeed, and the measurement frequency according to the obstacle distance,and updates the measurement record according to at least one of theadjusted movement path, movement speed, and measurement frequency andthe obstacle distance.
 14. The network quality measurement system ofclaim 12, wherein the controller receives an external command, adjustsat least one of the movement path, the movement speed, and themeasurement frequency according to the external command, and updates themeasurement record according to at least one of the adjusted movementpath, movement speed, and measurement frequency.
 15. The network qualitymeasurement system of claim 12, wherein the controller samples andtransforms the network quality data of the vehicle device in the spaceaccording to a predetermined sub-region size to determine whether thenetwork quality in the space is changed.
 16. The network qualitymeasurement system of claim 15, wherein the controller cuts the spaceinto a plurality of sub-regions according to the sub-region size,obtains the coordinate information of the vehicle device according tothe measurement timestamp correspondingly, determines that the vehicledevice falls in each of the plurality of sub-regions according to thecoordinate information, so as to obtain a timestamp corresponding to thevehicle device entering and leaving each of the sub-regions in themeasurement timestamp, classifies the network quality data according tothe timestamp, so that the classified network quality data correspondsto each of the sub-regions, and calculates at least one qualitymeasurement value corresponding to each of the sub-regions according tothe classified network quality data, and generates a spatial measurementrecord matrix corresponding to the at least one quality measurementvalue.
 17. The network quality measurement system of claim 16, whereinthe controller compares the at least one quality measurement value of anadjacent sub-region, and when a difference between the at least onequality measurement value of the adjacent sub-region is greater than athreshold value, the controller determines that the network quality inthe space is changed.
 18. The network quality measurement system ofclaim 16, wherein the controller compares the at least one qualitymeasurement value of an adjacent sub-region, and when a differencebetween the at least one quality measurement value of the adjacentsub-region is greater than a threshold value, the controller adjusts thesub-region size, and cuts the space into a plurality of sub-regionsaccording to the adjusted sub-region size.
 19. The network qualitymeasurement system of claim 16, wherein the vehicle device furthercomprises: an image capture device configured to capture an image duringthe movement.
 20. The network quality measurement system of claim 19,further comprising: a terminal device, comprising: an image processorcoupled to the memory and the image capture device and configured to:receive the image and obtain an image timestamp of the image,corresponding the coordinate information of the vehicle device to theimage timestamp, obtain an attitude parameter of the vehicle device anda lens parameter of the image capture device according to the image,calculate an angle of view position in a three-dimensional spaceaccording to the attitude parameter and the lens parameter, obtain theat least one quality measurement value corresponding to a plurality ofsub-regions in the angle of view position according to the spatialmeasurement record matrix, classify the at least one quality measurementvalue so that the at least one quality measurement value corresponds toa color mark of different colors or a material mark of differentmaterials according to a category, and combine the at least one qualitymeasurement value after corresponding to the color mark or the materialmark and the image to generate a visualized image; and an image displaycoupled to the image processor and configured to display the visualizedimage.